Tag Archives: American Marketing Association

Big Data is Science Fiction Already Here

Big data is a tech buzzword that instills varied emotions in the business community, from excitement to cynicism. To some, it’s a new era that is either:

An incoming apocalypse (there goes our privacy!)
An incoming paradise (there goes their privacy!)

The hype has arrived, but the era of big data is not exactly here although it’s here—yet organizations better be ready for it or they’ll go the way of the Myspace dodo (or something like that, according to some digital prophets).

Okay, but what exactly is big data?

Big data may seem like actualized science fiction, and in actuality science fiction is a suitable means of crystalizing technological advances (and sometimes inspire them, such as in the case of some of the first cell phones, inspired by Star Trek). By taking a look at some groundbreaking science fiction movies, one can easily (and perhaps ironically) demystify the notion of big data.

First, a technical definition of big data: There isn’t one.

To illustrate the murkiness of defining big data, Forbes published 12 Big Data Definitions: What’s Yours? The piece proffered several characterizations, from bland Wikipedia to eccentric scientists conjuring terms when pausing in their search for the next God particle. Nobody fully agrees, and in fact nobody even knows if the term should be capitalized.

In the most simplistic way, big data could be defined as this:

A lot of big-ass information floating around in digital form that if corralled could be useful for data research and statistical analysis…but it takes a big ass a machine as large as Skynet to successfully store, handle, and make sense of all this big ass information.

To wit: The big-ass information is basically a universe of records, forms, surveys, applications, and what not, just waiting to be organized and analyzed. This, in theory, can potentially make an organization near-prophetic (and others maybe just efficient). Big data could be a boon to such bulky industries like healthcare, military, human resources, and consumer insights.

At an American Marketing Conference, Justin Massa, CEO of Food Genius, adroitly defined big data as having five “V’s”:

Volume: The most obvious of the 5, there’s lots of data!
Velocity: The data grows and changes quickly.
Variety: Data comes in a variety of structures, creating complexity.
Veracity: “Dirty” data may need to be cleaned up.
Value: All that data is only useful if you can extract value.

(Perhaps coming close to the most suitable definition of big data, Massa added that it is any data that is too large to fit into an Excel file).

All of this ought to be useful. But again, glancing at science fiction movies we can see the allure and even potential of big data:

The Matrix

Matrix and big data

This iconic movie about rebellious machines is typified by those green digital numbers floating before the screen. The numbers clearly represent big data. Even the Matrix itself cannot fully manage this big-ass information with all its data mining  (as seen by mathematical anomalies, rebellious programs like the Oracle and the Merovingian, and its many (many) climaxes in the plot). In the end (or after the first and third movie of the series), it’s actually the protagonist Neo who is able to process all the big data, becoming the ultimate tragic hero.

Lesson: No matter how efficient the technology, it still takes a human to understand the big picture of big data.

Pi

Pi and big data

Many might not remember Darren Aronofsky’s directorial debut. The film is certainly an engaging exercise in understanding big data. The plot centers on the protagonist Max and his computer Euclid’s ability to predict the future movement of big data anywhere (something already in our world, called predictive analytics). As an example, Max is able to make stock predictions based on the calculations of Euclid. Could this eventually get him to unravel the secrets of the cosmos, all one big mathematical equation? In any event, all of this gets Max in some trouble with the authorities, business moguls, and even Jewish Kabbalists.

Lesson: The universe is one big, big data processor, unmatched by any mortal device. Be nice to it.

Transcendence

Transcendence and big data

The latest bomb by Johnny Depp deals with the concept of Transhumanism, where computer and human become united in byte bliss. Depp’s character is the first to undergo this phenomena, immediately enjoying access to almost limitless information while struggling to retain his humanity (and girlfriend). Ultimately, it’s humanity’s ignorance that aborts so much potential, not the information being gathered and utilized.

Lesson: Turning back the clock on big data could be unwise, but not as much as not raising one’s empathy in any new era.

Lucy

Lucy and big data

In this movie, it’s not curiosity or miffed machines that causes the leverage of big data. It’s motherhood. Lucy (played by Scarlett Johansson not being the Black Widow) is accidentally injected with massive amounts of CPh4, a drug found in expectant mothers that accelerates brain activity. Lucy acquires so much brain activity that she is able to tap into all the information of the planet and become basically divine (and still able to karate-kick bad guys, as happens in any Luc Besson film).

Lesson: Intelligence has to be nurtured like a child even before birth, so does big data.

None of the mentioned films really grants a pedantic definition of big data. Yet in a very Joseph Campbell-style, they make the idea of big data approachable, understandable, and even romantic. Part of the function of mythic art is to bestow humanity’s a workable relation the changing environment. These films are certainly mythic art; and science fiction additionally offers possible results in didactic flavors without us having to undergo them.

Ultimately, big data is nothing but a natural stage of the information era, another tool of qualitative market research. It’s just not as sexy as social media or smartphones (and no one still agrees on capitalizing those two).

There is one specific future we can depend on when it comes to big data, and all the cited movies agree: It’s not so much how big data acts that matters, it’s how humanity reacts to it that will make the difference.

The path to big data will certainly be a fine path between an apocalypse and a paradise.

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The Pros and Cons of Surveys

 

Research professionals who have been in the business for years have seen survey popularity with consumers ebb and flow. When surveys were new, they were fun and it was easy to find survey participants to complete them. However, it became evident that survey data collection was becoming more and more challenging, due to other activities on the calendar that became a huge distraction to the average consumer.

 

How do researchers compete for the consumer’s time effectively? Respondents who complete a survey are often rewarded for their time and participation. At a time when the economy was somewhat sluggish, survey honorariums became a huge attraction with research participants and viewed by some as a way to earn some income on the side. A focus group participant, for example, can earn anywhere from $50 and up for their time. With the growth of social networks, taking a survey has become easier than ever and many research firms, including qSample, take full advantage of the methodology.

 

For this post, we explored the pros and cons of surveying.survey_news

 

Pros:

 

Surveys allow marketers to gather many different opinions from a wide-market spread, or from many different markets. Running around the mall with a clipboard to complete surveys can sometimes lead to skewed conclusions, since the majority of survey participants will consist of local residents. While this might work if the research requires speaking with local area residents, an online survey is probably a better, cheaper and more effective method to reach a broader audience.

 

Surveys allow for sampling within certain regions, if needed. Surveys can be initiated in certain regions only, if needed. In fact, panel providers, like qSample, can target respondents’ zip codes for very selective geographic studies. If a respondent needs to live in Midland, TX because a researcher wants to discover the draw of living there, a researcher can pull respondents from that area only.

 

Surveys ensure that all respondents are answering the same questions. This is important so that the resulting data is very clear (i.e. 40% of respondents said that they like to pack a lunch and 60% of them do not like to pack a lunch). If participants receive different questions and options to respond, the survey results become null.

 

With modern surveys, marketers can compile results quickly and use technology to see trends. Gone are the days of hand-counting checkmarks in certain columns and then creating reports about those results (unless one IS running around a mall with a clipboard).

qSample has unique technology that allows instant graphing of results as they come in. Those results are open to all team members involved so that adjustments can be made if needed and communication is clear. Because qSample already has active panel members ready to participate and great software, surveys can often be completed within days.

 

Surveys protect respondent’s personal information and do not affiliate information with a name. Online surveys in particular guard the consumer’s private information so that it cannot be sold, rented or tampered with. There is no paper trail on respondents. Although certain demographics might be tapped for a particular survey, contributor’s contact information is kept separate from the results lessening the potential fear of identity theft, inherent bias, etc.

 

Cons:

 

Respondents may be biased when answering questions. Although researchers, not unlike lawyers in a jury selection process, can attempt to find any bias before running a survey, this isn’t always possible. If the goal is to find consumers who love General Mills, a marketer will initially ask consumers if they buy General Mills products before sending them to the rest of the questions and of course, it’s possible some would claim to buy the brand when they really don’t. This would immediately skew the results. Surveys must operate on the assumption that most contributors are answering to the best of their knowledge and allow for a small margin of nuances.

 

If survey answers are multiple choice, some answers may not be listed. Many wonder why there is not an answer that fits them on some survey questions. It is because the researcher wants participants to fit into the categories offered. Although they recognize that not all participants will comply, they want to connect mostly with the people that do fit into those categories. The best surveys will have an “other” or a “none of the above” option.

 

Respondents sometimes skip or are untruthful about personal questions, like income and age. Respondents have a natural inclination to be untruthful if they perceive that the question crosses a line. Annual income ranges are an example of this. Does it matter? Perhaps. Market Researchers know this and can work with it. If researchers want to know if those who make more than $100,000 like to buy a certain car or not, the survey should be approached with that qualification up front by gathering respondents who make that verified income range before even beginning the survey.

 

Marketers can be biased when putting together respondent qualifications or survey questions. It exists and is sometimes hard to pin down, but of course there can be bias when writing a survey. In addition, questions can be leading, which makes for a poor tool to gather unbiased data.

 

Sometimes surveys don’t hold consumer’s attention long enough to complete. Ideally, a survey is created with this in mind and retains the interest of respondents. Minimizing respondent fatigue and making the survey as user friendly as possible is paramount to getting the best responses possible. qSample keeps this in mind before fielding any surveys and employs several different tactics to keep respondents engaged.

 

Understanding the potential cons of surveys, market researchers have implemented methods to minimize these issues and gather accurate data.  With the large reach of surveys, and especially qSample’s online and mobile options, marketers can reach the exact market of people that they need and gather the best data possible.

 

The Nimble Elephant: Big Data and Agile Marketing

On Monday September 9, 2013, the qSample team attended the American Marketing Association “Evening with Experts at 1871: The Age of Agile Marketing.” The speakers were Justin Massa, CEO of Food Genius and Chris Young, Senior Director Global Menu Services at McDonald’s. The presenters showed us how big data can be leveraged to facilitate agile marketing.

What is agile marketing? No, it’s not practicing yoga postures while drafting a marketing plan. According to agilemarketing.net the goals “are to improve the speed, predictability, transparency, and adaptability to change of the marketing function.” Agile marketing is inspired by the values of agile development:

Agile Marketing

Responding to change over following a plan
Rapid iterations over Big-Bang campaigns
Testing and data over opinions and conventions
Numerous small experiments over a few large bets
Individual interactions over target markets
Collaboration over silos and hierarchy i

Agile-Marketing-Series-What-is-Agile-Marketing

Basing marketing decisions on data rather than instinct was the theme of the night. Justin Massa emphasized that Food Genius is, above all, a technology company that extracts insights from an enormous amount of restaurant menu data from numerous sources such as GrubHub and presents them in such a way that a client can understand. Massa works with what is known as big data, which he describes in layman’s terms as data that you can’t download in an Excel file. He referenced the 5 V’s of big data to illustrate its core functions.

The Five V’s of Big Data

Volume: The most obvious of the 5, there’s lots of data!
Velocity: The data grows and changes quickly.
Variety: Data comes in a variety of structures, creating complexity.
Veracity: “Dirty” data may need to be cleaned up.
Value: All that data is only useful if you can extract value.

big-data-elephant-dreamstime_xs_27975666

Massa implored marketers armed with valuable data to stop asking “why?” and to be satisfied with just the “what.” He argues that identifying the trend is enough. For example, wraps are one of the fasted growing menu items in the United States. You don’t need to know why wraps are so popular. Is it the low carb craze, the gluten-free trend, the salad-sandwich hybrid appeal? Doesn’t matter. Just identify the “what” and forget about the “why.” The “why” he says, will just slow you down and decrease your agility. Of course, this may be because big data alone typically can’t give you the “why,” even if you needed it. Big data plays a very important role in agile marketing, but for most marketers, it will not be the only source of data.

The truth is that there are many segments that simply don’t yet have an accessible data infrastructure, let alone a specialty company like Food Genius tracking and making sense of the data. If you’ve got a niche audience, sometimes the easiest thing to do is ask your exact target the exact questions you need answered, and you can just as easily ask “what” and “why” while you’re at it. For example, if you need a group of gamers to tell you what they think of your new product prototype, big data isn’t going to help.

qSample specializes in sample group acquisition and specialty panel management and recruitment. With 10 specialty panels including Homeowners, Baby Boomers, Campus Universe, Wine Opinions, Voters, Contractors, Gamers, Mobile, Small Biz Opinions and Travelers, plus a suite of survey software you can get the exact insights you need from the exact group you need to reach. The qSample mobile reporting app allows you to see your data in real time in vivid easy-to-understand charts and graphs. With quick turnaround and real-time data, survey research will enhance, not impair, your agility.

Remember agile value #5, “numerous small experiments over a few large bets”? To be an agile marketer, Massa tells us to eat the elephant one bite at a time. His slideshow image of elephant soup got some awws from the audience.

eat_the_elephant-300x204

McDonald’s knows better to bite off more than they can chew. Chris Young, Senior Director Global Menu Services at McDonald’s piggybacked off of Massa’s wrap example and explained that wraps were introduced country by country in European markets before introducing to U.S. restaurants.

In another example, Young pointed out that even McDonald’s didn’t dive headfirst into offering fruit smoothies. The company had big ambitions for their beverage line-up, but started first with perfecting their coffee recipe before moving into Frappes. With growing beverage success, they then introduced fruit smoothies which could be made using the existing Frappe machines. Young also pointed out that it’s often logistically imperative for McDonald’s to make small, market-by-market change simply because of the volume at which the company operates. There simply wouldn’t be enough strawberries on the planet to suddenly begin selling smoothies at every McDonald’s overnight.

Listening to Massa and Young share similar philosophies on agile marketing reinforces the universal value of the concept. Each company has put the principles of agile marketing into practice in different ways, as they each face different challenges. Traditional market researchers have had to become more nimble as well, as online and mobile surveys promising quick results have become the standard. The overall message is to utilize data to make decisions and to move quickly but make small changes, treating each move as an experiment that will guide future growth.

i http://agilemarketing.net/what-is-agile-marketing/

by Stacy Sherwood